Record Details

Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images

MELSpace

View Archive Info
 
 
Field Value
 
Title Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images
 
Creator Xin, Fengfei
 
Contributor Xiao, Xiangming
Zhao, Bin
Miyata, Akira
Baldocchi, Dennis
Knox, Sara
Kang, Minseok
Shim, Kyo-Moon
Min, Sunghyun
Chen, Bangqian
Li, Xiangping
Wang, Jie
Dong, Jinwei
Biradar, Chandrashekhar
 
Subject light use efficiency
chlorophyll
multi-site co2 fluxes
vegetation photosynthesis model
 
Description Accurate information on the gross primary production (GPP) of paddy rice cropland is critical for assessing and monitoring rice growing conditions. The eddy co-variance technique was used to measure net ecosystem ex- change (NEE) of CO2 between paddy rice croplands and the atmosphere, and the resultant NEE data then partitioned into GPP (GPPEC) and ecosystem respiration. In this study, we first used the GPPEC data from four paddy rice flux tower sites in South Korea, Japan and the USA to evaluate the biophysical performance of three vegetation indices: Normalized Difference Vegetation Index (NDVI); Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) in terms of phenology (crop growing seasons) and GPPEC, which are derived from images taken by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. We also ran the Vegetation Photosynthesis Model (VPM), which is driven by EVI, LSWI, photosynthetically active radiation (PAR) and air temperature, to estimate GPP over multiple years at these four sites (GPPVPM). The 14 site-years of simulations show that the seasonal dynamics of GPPVPM successfully tracked the seasonal dynamics of GPPEC (R2 N 0.88 or higher). The cross-site comparison also shows that GPPVPM agreed reasonably well with the variations of GPPEC across both years and sites. The simulation results clearly demonstrate the potential of the VPM model and MODIS images for estimating GPP of paddy rice croplands in the monsoon climates of South Korea and Japan and the Mediterranean climate in California, USA. The application of VPM to regional simulations in the near future may provide crucial GPP data to support the studies of food security and cropland carbon cycle around the world.
 
Date 2017-03-01
2017-02-23T13:20:24Z
2017-02-23T13:20:24Z
 
Type Journal Article
 
Identifier https://mel.cgiar.org/dspace/limited
https://www.sciencedirect.com/science/article/pii/S0034425716304722
https://www.researchgate.net/publication/312333872_Modeling_gross_primary_production_of_paddy_rice_cropland_through_analyses_of_data_from_CO2_eddy_flux_tower_sites_and_MODIS_images
Fengfei Xin, Xiangming Xiao, Bin Zhao, Akira Miyata, Dennis Baldocchi, Sara Knox, Minseok Kang, Kyo-Moon Shim, Sunghyun Min, Bangqian Chen, Xiangping Li, Jie Wang, Jinwei Dong, Chandrashekhar Biradar. (1/3/2017). Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images. Remote Sensing of Environment, 190, pp. 42-55.
https://hdl.handle.net/20.500.11766/5915
Limited access
 
Language en
 
Format PDF
 
Publisher Elsevier
 
Source Remote Sensing of Environment;190,(2016) Pagination 42-55